Leading Business with Data LEE Wee Leong Associate Professor of Information Systems (Education) & Programme Director, MITB(Analytics) 1
Master of IT in Business (Analytics) 2
How Do We Make Decisions? 10% - Hard Facts 90% - Gut Feel * Economist Intelligence Unit, 2014 *40% of major decision making are based on gut feeling! * Accenture, 2008 12% - Hard Facts 88% - Gut Feel * Aspect Consulting, 1997 3
What is Data Analytics? DATA Statistical & Quantitative Analyses Fact-based Decisions & Actions Explanatory & Predictive Modeling Analytics is the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions. ~ Thomas H. Davenport ~ Competing on Analytics: The New Science of Winning 4
Why Data Analytics is HOT Now? Oracle Big Data Intel Inside Penti um Intel Inside Penti um 4 Intel Inside Core Duo 2 Intel Inside Core Quad 2 Intel Inside Core i5 Weka The University of Waikato SPSS Software IBM SAS Rapidminer IBM Watson KNIME Explosion of data Big Data Increase in Processing Power & Cheaper Storage Revolution Analytics Ease of Analyzing Data 5
What is BIG DATA? Volume Scale of Data Variety Different Forms of Data The FOUR V s of Big Data Velocity Analysis of Streaming Data Veracity Uncertainty of Data 6
Analytics Financial Industry Telco Consultancy Healthcare Retail Transportation & Logistics 7
MITB (Analytics) Curriculum Foundation Courses Analytics Framework & Business Context Data Analytics Lab Elective Courses Customer Analytics Operations Analytics Big Data: Tools & Techniques *(new) Visual Analytics Hands-on & Industry Linkage Internship/ Capstone Project Monthly industry seminars Full time : 1 year Part time : 2 years Introduction to Statistics Introduction to R Programming Text Analytics Social Analytics Applied Machine Learning *(new) Predictive Analytics using Simulation *(new) General and IT & Project courses
The Curriculum in a Nutshell B. Analytics Technology & B.1 Analytics Framework & Business Context B.2 Data Analytics Lab B.3 Customer Analytics & B.4 Operations Analytics & B.5 Big Data: Tools & Techniques B.6 Visual Analytics & B.7 Text Analytics & Equip B.8 Social with Analytics innovation, & IT and project management skills B.9 Applied Machine Learning B.10 Predictive Analytics using Simulation C. Information Technology C.1* Innovation C.2 Spreadsheet Modeling for Technology & Operations Decisions C.3 IT Project & Vendor C.4 Global Sourcing of Technology & Processes D. General for Technology & Operations D.1A* Financial Accounting D.1C* Accounting for T&O Managers D.2 Strategy & Organisation D.3 Finance for T&O Managers D.4* HRM for Technology & Operations Managers E. Internship / Capstone Project E.1 Internship Internship Job description definition Resume writing, internship application & interviews Industry attachment E.2 Capstone Project Project definition, development & critique workshops Industry expert seminars & company site visits Project Delivery 9
The Curriculum in a Nutshell B. Analytics Technology & B.1 Analytics Framework & Business Context B.2 Data Analytics Lab B.3 Customer Analytics & B.4 Operations Analytics & B.5 Big Data: Tools & Techniques B.6 Visual Analytics & B.7 Text Analytics & B.8 Social Analytics & B.9 Applied Machine Learning B.10 Predictive Analytics using Simulation C. Information Technology C.1* Innovation C.2 Spreadsheet Modeling for Technology & Operations Decisions C.3 IT Project & Vendor C.4 Global Sourcing of Technology & Processes Develop business management skills D. General for Technology & Operations D.1A* Financial Accounting D.1C* Accounting for T&O Managers D.2 Strategy & Organisation D.3 Finance for T&O Managers D.4* HRM for Technology & Operations Managers E. Internship / Capstone Project E.1 Internship Internship Job description definition Resume writing, internship application & interviews Industry attachment E.2 Capstone Project Project definition, development & critique workshops Industry expert seminars & company site visits Project Delivery 10
The Curriculum in a Nutshell B. Analytics Technology & B.1 Analytics Framework & Business Context B.2 Data Analytics Lab B.3 Customer Analytics & B.4 Operations Analytics & B.5 Big Data: Tools & Techniques B.6 Visual Analytics & B.7 Text Analytics & B.8 Social Analytics & B.9 Applied Machine Learning B.10 Predictive Analytics using Simulation C. Information Technology C.1* Innovation C.2 Spreadsheet Modeling for Technology & Operations Decisions C.3 IT Project & Vendor C.4 Global Sourcing of Technology & Processes D. General for Technology & Operations D.1A* Financial Accounting D.1C* Accounting for T&O Managers D.2 Strategy & Organisation D.3 Finance for T&O Managers D.4* HRM for Technology & Operations Managers Acquire hands-on industry experience, with internship opportunities for full-time students. E. Internship / Capstone Project E.1 Internship Internship Job description definition Resume writing, internship application & interviews Industry attachment E.2 Capstone Project Project definition, development & critique workshops Industry expert seminars & company site visits Project Delivery 11
MITB (Analytics) At a Glance First Master Program in Analytics in Asia Launched in Jan 2011 10 th intake (Aug 2016) Our case won TUN teaching innovation award 2013 Our simulation games shortlisted for Wharton-QS Stars Reimagine Education Awards 2015 Largest ecosystem in Data & Decision Analytics related research Wide selection of internship opportunity
Summary Benefits for commuters: With real-time commuters data, model developed will be able to give commuters a good gauge of the average waiting time at the train stations. New or existing mobile applications can be developed to tap into this useful information. Benefits for train operators: The simulation model can be used as a test bed to test various scenarios by varying some operational conditions like: Train capacity (new models or add seats) Inter-station travelling time (change speed of trains)